• Journal of Educational Research in Mathematics
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• v.23 no.2
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• pp.153-171
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• 2013

The purpose of this study is to investigate characteristics of students' problem solving processes based on their mathematical thinking styles and thus to provide implications for teachers regarding how to employ multiple representations. In order to analyze these characteristics, 202 university freshmen were recruited for a paper-and-pencil survey. The participants were divided into four groups on a mathematical-thinking-style basis. There were two students in each group with a total of eight students being interviewed. Results show that mathematical thinking styles are related to defining a mathematical concept, problem solving in relation to representation, and translating between mathematical representations. These results imply methods of utilizing multiple representations in learning and teaching mathematics by embodying Dienes' perceptual variability principle.

• Journal of Practical Engineering Education
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• v.10 no.1
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• pp.35-39
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• 2018

More and more universities are enforcing SW education for non-major undergraduates. However, they are experiencing difficulties in educating non-major students to understand computational thinking processes. In this paper, we did not use the mathematical operation problem to solve this problem. And we proposed a basic problem-solving process teaching method based on computational thinking using simple physical devices. In the proposed educational method, we teach a LED circuit using an Arduino board as an example. And it explains the problem-solving process with computational thinking. Through this, students learn core computational thinking processes such as abstraction, problem decomposition, pattern recognition and algorithms. By applying the proposed methodology, students can gain the concept and necessity of computational thinking processes without difficulty in understanding and analyzing the given problem.

• Journal of Gifted/Talented Education
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• v.25 no.4
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• pp.581-605
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• 2015

The purpose of this study is to build an instruction method focused on the mathematical process and apply it to 12, 5-year-olds from Kindergarten located in Seoul with a view to explore the changes in their mathematical thinking. In addition, surveys with parents and teachers, as well as those conducted in the field of early childhood education, were conducted to analyze the current situation. The effects focused on the five mathematical processes, namely problem solving, reasoning and proof, connecting, representing and communication was found to help the interactions between teacher-child and child-child stimulate the mathematical thinking of the children and induce changes. The mathematical process-focused instruction aimed to advance mathematical thinking internalized mathematical knowledge, presented an integrated problematic situation, and empathized the mathematical process, which enabled the children to solve the problem by working together with peers. As such, the mathematical thinking of the children was integrated and developed within the process of a positive change in the mathematical attitude in which mathematical knowledge is internalized through mathematical process.

• Research in Mathematical Education
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• v.19 no.1
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• pp.61-79
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• 2015

This study discussed about how pseudo-thinking process actually occurs in the mind of the students, used Piaget's frame work of the assimilation and accommodation process. The data collection is conducted using Think-Out-Loud (TOL) method. The study reveals that pseudo thinking process of covariational reasoning occurs originally from incomplete assimilation, incomplete accommodation process or both. Based on this, three models of incomplete thinking structure constructions are established: (1) Deviated thinking structure, (2) Incomplete thinking structure on assimilation process, and (3) Incomplete thinking structure on accommodation process.

• Korean Journal of Child Studies
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• v.28 no.4
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• pp.319-331
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• 2007

This review of literature establishes a contemporary meaning of mathematical problem solving including young children's mathematical problem solving processes/assessments and teaching strategies. The contemporary meaning of mathematical problem solving involves complicated higher thinking processes. Explanations of the mathematical problem solving processes of young children include the four steps suggested by $P{\acute{o}}lya$(1957) : understand the problem, devise a plan, carry out the plan, and review/extend the plan. Assessments of children's mathematical problem solving include both the process and the product of problem solving. Teaching strategies to support children's mathematical problem solving include mathematical problems built upon children's daily activities, interests, and questions and helping children to generate new approaches to solve problems.

• The Mathematical Education
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• v.63 no.2
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• pp.233-254
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• 2024

This paper delves into the symbiotic integration of coding and mathematics education, aimed at cultivating computational thinking and enriching mathematical problem-solving proficiencies. We have identified a corpus of scholarly articles (n=38) disseminated within the preceding two decades, subsequently culling a portion thereof, ultimately engendering a contemplative analysis of the extant remnants. In a swiftly evolving society driven by the Fourth Industrial Revolution and the ascendancy of Artificial Intelligence (AI), understanding the synergy between these domains has become paramount. Mathematics education stands at the crossroads of this transformation, witnessing a profound influence of AI. This paper explores the evolving landscape of mathematical cognition propelled by AI, accentuating how AI empowers advanced analytical and problem-solving capabilities, particularly in the realm of big data-driven scenarios. Given this shifting paradigm, it becomes imperative to investigate and assess AI's impact on mathematics education, a pivotal endeavor in forging an education system aligned with the future. The symbiosis of AI and human cognition doesn't merely amplify AI-centric thinking but also fosters personalized cognitive processes by facilitating interaction with AI and encouraging critical contemplation of AI's algorithmic underpinnings. This necessitates a broader conception of educational tools, encompassing AI as a catalyst for mathematical cognition, transcending conventional linguistic and symbolic instruments.

• The Mathematical Education
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• v.58 no.4
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• pp.483-505
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• 2019

Across the world, there is a movement to incorporate computational thinking(CT) into school curricula, and math is at the heart of this movement. This paper reviewed the meanings of CT based on the point of view of Jeanette Wing, and the trend of domestic and international studies that incorporated CT into the field of mathematics education was analyzed to provide implications for mathematics education and future research. Results indicated that the meaning of CT, defined by mainly computer educators, varied in their operationalization of CT. Although CT and mathematical thinking generally have common points that are oriented toward problem solving, there were differences in the way of abstraction that is central to the two thinking processes. The experimental studies on CT in the field of mathematics education focused mainly on the development of students' cognitive capacities and affective domains through programming(coding). Furthermore, the previous studies were mainly conducted on students in school, and the studies conducted in the context of higher education, including pre-service and in-service teachers, were insufficient. Implications for mathematics teacher educators and teacher education as well as the relationship between CT and mathematical thinking are discussed.

• The Mathematical Education
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• v.42 no.5
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• pp.623-636
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• 2003

Metacognition is defined to be 'thinking about thinking' and 'knowing what we know and what we don't know'. It was verified that the metacognitive abilities of high school students can be improved via instruction. The purpose of this article is to investigate a new method for activating the metacognitive abilities that play a key role in the Mathematical Problem Solving Process(MPSP). Hyunsung participated in the MPSP using Visual Basic Programming. He actively participated in the MPSP. There are sufficient evidences about activating the metacognitive abilities via the activity processes and interviews. In solving mathematical problems, he had basic metacognitive abilities in the stage of understanding mathematical problems; through the experiments, he further developed his metacognitive abilities and successfully transferred them to general mathematical problem solving.

• The Mathematical Education
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• v.53 no.2
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• pp.275-290
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• 2014

This study investigated the types of the 3D geometric thinking and spatial reasoning through the observation of the 2D representing activities for representing the 3D geometrical objects with preservice secondary mathematics teachers. For this purpose, the 43 sophomoric students in college of education were divided into 10 groups and observed their group task performance on the basis of the representation they used. Observed processes were all recorded and the participants were interviewed based on the task. As a result, the role of physical object that becoming the object of geometric thinking and spatial reasoning, and diverse strategies and phenomena of the process that representing the 3D geometric figures in 2D were discovered. Furthermore, these processes of representing were assumed to be influenced by experience and study practice of students, and various forms of representing process were also discovered in the process of small group activities.

• Communications of Mathematical Education
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• v.37 no.2
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• pp.257-276
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• 2023

Mathematical modeling can be described as a series of processes in which real-world problem situations are understood, interpreted using mathematical methods, and solved based on mathematical models. The effectiveness of mathematics instruction using mathematical modeling has been demonstrated through prior research. This study aims to explore insights for mathematical modeling instruction by analyzing the metacognitive characteristics shown in the mathematical modeling cycle, according to the mathematical thinking styles of elementary math gifted students. To achieve this, a mathematical thinking style assessment was conducted with 39 elementary math gifted students from University-affiliated Science Gifted Education Center, and based on the assessment results, they were classified into visual, analytical, and mixed groups. The metacognition manifested during the process of mathematical modeling for each group was analyzed. The analysis results revealed that metacognitive elements varied depending on the phases of modeling cycle and their mathematical thinking styles. Based on these findings, didactical implications for mathematical modeling instruction were derived.